cointegrated_roberta-base-formality-finetuned-lora-tweet_eval_hate
This model is a fine-tuned version of cointegrated/roberta-base-formality on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.735
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0004
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
accuracy | train_loss | epoch |
---|---|---|
0.447 | None | 0 |
0.714 | 0.6180 | 0 |
0.717 | 0.5041 | 1 |
0.718 | 0.4541 | 2 |
0.735 | 0.4284 | 3 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2
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Model tree for TransferGraph/cointegrated_roberta-base-formality-finetuned-lora-tweet_eval_hate
Base model
cointegrated/roberta-base-formalityDataset used to train TransferGraph/cointegrated_roberta-base-formality-finetuned-lora-tweet_eval_hate
Evaluation results
- accuracy on tweet_evalvalidation set self-reported0.735